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Sentiment of Emojis
There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4671607/ https://www.ncbi.nlm.nih.gov/pubmed/26641093 http://dx.doi.org/10.1371/journal.pone.0144296 |
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author | Kralj Novak, Petra Smailović, Jasmina Sluban, Borut Mozetič, Igor |
author_facet | Kralj Novak, Petra Smailović, Jasmina Sluban, Borut Mozetič, Igor |
author_sort | Kralj Novak, Petra |
collection | PubMed |
description | There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). About 4% of the annotated tweets contain emojis. The sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar. |
format | Online Article Text |
id | pubmed-4671607 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-46716072015-12-10 Sentiment of Emojis Kralj Novak, Petra Smailović, Jasmina Sluban, Borut Mozetič, Igor PLoS One Research Article There is a new generation of emoticons, called emojis, that is increasingly being used in mobile communications and social media. In the past two years, over ten billion emojis were used on Twitter. Emojis are Unicode graphic symbols, used as a shorthand to express concepts and ideas. In contrast to the small number of well-known emoticons that carry clear emotional contents, there are hundreds of emojis. But what are their emotional contents? We provide the first emoji sentiment lexicon, called the Emoji Sentiment Ranking, and draw a sentiment map of the 751 most frequently used emojis. The sentiment of the emojis is computed from the sentiment of the tweets in which they occur. We engaged 83 human annotators to label over 1.6 million tweets in 13 European languages by the sentiment polarity (negative, neutral, or positive). About 4% of the annotated tweets contain emojis. The sentiment analysis of the emojis allows us to draw several interesting conclusions. It turns out that most of the emojis are positive, especially the most popular ones. The sentiment distribution of the tweets with and without emojis is significantly different. The inter-annotator agreement on the tweets with emojis is higher. Emojis tend to occur at the end of the tweets, and their sentiment polarity increases with the distance. We observe no significant differences in the emoji rankings between the 13 languages and the Emoji Sentiment Ranking. Consequently, we propose our Emoji Sentiment Ranking as a European language-independent resource for automated sentiment analysis. Finally, the paper provides a formalization of sentiment and a novel visualization in the form of a sentiment bar. Public Library of Science 2015-12-07 /pmc/articles/PMC4671607/ /pubmed/26641093 http://dx.doi.org/10.1371/journal.pone.0144296 Text en © 2015 Kralj Novak et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Kralj Novak, Petra Smailović, Jasmina Sluban, Borut Mozetič, Igor Sentiment of Emojis |
title | Sentiment of Emojis |
title_full | Sentiment of Emojis |
title_fullStr | Sentiment of Emojis |
title_full_unstemmed | Sentiment of Emojis |
title_short | Sentiment of Emojis |
title_sort | sentiment of emojis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4671607/ https://www.ncbi.nlm.nih.gov/pubmed/26641093 http://dx.doi.org/10.1371/journal.pone.0144296 |
work_keys_str_mv | AT kraljnovakpetra sentimentofemojis AT smailovicjasmina sentimentofemojis AT slubanborut sentimentofemojis AT mozeticigor sentimentofemojis |